8 Search Results for "Oudot, Steve Y."

Document
DOI: 10.4230/LIPIcs.SoCG.2025.29
Sparsification of the Generalized Persistence Diagrams for Scalability Through Gradient Descent

Authors: Mathieu Carrière, Seunghyun Kim, and Woojin Kim

Published in: LIPIcs, Volume 332, 41st International Symposium on Computational Geometry (SoCG 2025)

Abstract
The generalized persistence diagram (GPD) is a natural extension of the classical persistence barcode to the setting of multi-parameter persistence and beyond. The GPD is defined as an integer-valued function whose domain is the set of intervals in the indexing poset of a persistence module, and is known to be able to capture richer topological information than its single-parameter counterpart. However, computing the GPD is computationally prohibitive due to the sheer size of the interval set. Restricting the GPD to a subset of intervals provides a way to manage this complexity, compromising discriminating power to some extent. However, identifying and computing an effective restriction of the domain that minimizes the loss of discriminating power remains an open challenge. In this work, we introduce a novel method for optimizing the domain of the GPD through gradient descent optimization. To achieve this, we introduce a loss function tailored to optimize the selection of intervals, balancing computational efficiency and discriminative accuracy. The design of the loss function is based on the known erosion stability property of the GPD. We showcase the efficiency of our sparsification method for dataset classification in supervised machine learning. Experimental results demonstrate that our sparsification method significantly reduces the time required for computing the GPDs associated to several datasets, while maintaining classification accuracies comparable to those achieved using full GPDs. Our method thus opens the way for the use of GPD-based methods to applications at an unprecedented scale.
Cite as

Mathieu Carrière, Seunghyun Kim, and Woojin Kim. Sparsification of the Generalized Persistence Diagrams for Scalability Through Gradient Descent. In 41st International Symposium on Computational Geometry (SoCG 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 332, pp. 29:1-29:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{carriere_et_al:LIPIcs.SoCG.2025.29,
  author =	{Carri\`{e}re, Mathieu and Kim, Seunghyun and Kim, Woojin},
  title =	{{Sparsification of the Generalized Persistence Diagrams for Scalability Through Gradient Descent}},
  booktitle =	{41st International Symposium on Computational Geometry (SoCG 2025)},
  pages =	{29:1--29:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-370-6},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{332},
  editor =	{Aichholzer, Oswin and Wang, Haitao},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2025.29},
  URN =		{urn:nbn:de:0030-drops-231810},
  doi =		{10.4230/LIPIcs.SoCG.2025.29},
  annote =	{Keywords: Multi-parameter persistent homology, Generalized persistence diagram, Generalized rank invariant, Non-convex optimization, Gradient descent}
}
Document
DOI: 10.4230/LIPIcs.SoCG.2025.58
Tracking the Persistence of Harmonic Chains: Barcode and Stability

Authors: Tao Hou, Salman Parsa, and Bei Wang

Published in: LIPIcs, Volume 332, 41st International Symposium on Computational Geometry (SoCG 2025)

Abstract
The persistence barcode is a topological descriptor of data that plays a fundamental role in topological data analysis. Given a filtration of data, the persistence barcode tracks the evolution of its homology groups. In this paper, we introduce a new type of barcode, called the harmonic chain barcode, which tracks the evolution of harmonic chains. In addition, we show that the harmonic chain barcode is stable. Given a filtration of a simplicial complex of size m, we present an algorithm to compute its harmonic chain barcode in O(m³) time. Consequently, the harmonic chain barcode can enrich the family of topological descriptors in applications where a persistence barcode is applicable, such as feature vectorization and machine learning.
Cite as

Tao Hou, Salman Parsa, and Bei Wang. Tracking the Persistence of Harmonic Chains: Barcode and Stability. In 41st International Symposium on Computational Geometry (SoCG 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 332, pp. 58:1-58:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{hou_et_al:LIPIcs.SoCG.2025.58,
  author =	{Hou, Tao and Parsa, Salman and Wang, Bei},
  title =	{{Tracking the Persistence of Harmonic Chains: Barcode and Stability}},
  booktitle =	{41st International Symposium on Computational Geometry (SoCG 2025)},
  pages =	{58:1--58:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-370-6},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{332},
  editor =	{Aichholzer, Oswin and Wang, Haitao},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2025.58},
  URN =		{urn:nbn:de:0030-drops-232100},
  doi =		{10.4230/LIPIcs.SoCG.2025.58},
  annote =	{Keywords: Persistent homology, harmonic chains, topological data analysis}
}
Document
DOI: 10.4230/LIPIcs.SoCG.2025.6
A Sparse Multicover Bifiltration of Linear Size

Authors: Ángel Javier Alonso

Published in: LIPIcs, Volume 332, 41st International Symposium on Computational Geometry (SoCG 2025)

Abstract
The k-cover of a point cloud X of ℝ^d at radius r is the set of all those points within distance r of at least k points of X. By varying r and k we obtain a two-parameter filtration known as the multicover bifiltration. This bifiltration has received attention recently due to being choice-free and robust to outliers. However, it is hard to compute: the smallest known equivalent simplicial bifiltration has O(|X|^{d+1}) simplices. In this paper we introduce a (1+ε)-approximation of the multicover bifiltration of linear size O(|X|), for fixed d and ε. The methods also apply to the subdivision Rips bifiltration on metric spaces of bounded doubling dimension yielding analogous results.
Cite as

Ángel Javier Alonso. A Sparse Multicover Bifiltration of Linear Size. In 41st International Symposium on Computational Geometry (SoCG 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 332, pp. 6:1-6:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{alonso:LIPIcs.SoCG.2025.6,
  author =	{Alonso, \'{A}ngel Javier},
  title =	{{A Sparse Multicover Bifiltration of Linear Size}},
  booktitle =	{41st International Symposium on Computational Geometry (SoCG 2025)},
  pages =	{6:1--6:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-370-6},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{332},
  editor =	{Aichholzer, Oswin and Wang, Haitao},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2025.6},
  URN =		{urn:nbn:de:0030-drops-231587},
  doi =		{10.4230/LIPIcs.SoCG.2025.6},
  annote =	{Keywords: Multicover, Approximation, Sparsification, Multiparameter persistence}
}
Document
DOI: 10.4230/LIPIcs.SoCG.2025.35
A Theory of Sub-Barcodes

Authors: Oliver A. Chubet, Kirk P. Gardner, and Donald R. Sheehy

Published in: LIPIcs, Volume 332, 41st International Symposium on Computational Geometry (SoCG 2025)

Abstract
The primary tool in topological data analysis (TDA) is persistent homology, which involves computing a barcode - often from point-cloud or scalar field data - that serves as a topological signature for the underlying function. In this work, we introduce sub-barcodes and show how they arise naturally from factorizations of persistence module homomorphisms. We show that, as a partial order induced by factorizations, the relation of being a sub-barcode is strictly stronger than the rank invariant, and we apply sub-barcode theory to the problem of inferring information about the barcode of an unknown Lipschitz function from samples. The advantage of this approach is that it permits strong guarantees - with no noise - while requiring no sampling assumptions, and the resulting barcode is guaranteed to be a sub-barcode of every Lipschitz function that agrees with the data. We also present an algorithmic theory that allows for the efficient approximation of sub-barcodes using filtered Delaunay triangulations for Euclidean inputs.
Cite as

Oliver A. Chubet, Kirk P. Gardner, and Donald R. Sheehy. A Theory of Sub-Barcodes. In 41st International Symposium on Computational Geometry (SoCG 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 332, pp. 35:1-35:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{chubet_et_al:LIPIcs.SoCG.2025.35,
  author =	{Chubet, Oliver A. and Gardner, Kirk P. and Sheehy, Donald R.},
  title =	{{A Theory of Sub-Barcodes}},
  booktitle =	{41st International Symposium on Computational Geometry (SoCG 2025)},
  pages =	{35:1--35:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-370-6},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{332},
  editor =	{Aichholzer, Oswin and Wang, Haitao},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2025.35},
  URN =		{urn:nbn:de:0030-drops-231873},
  doi =		{10.4230/LIPIcs.SoCG.2025.35},
  annote =	{Keywords: Topology, Topological Data Analysis, Persistent Homology, Persistence Modules, Barcodes, Sub-barcodes, Factorizations, Lipschitz Extensions}
}
Document
DOI: 10.4230/LIPIcs.SoCG.2025.64
Super-Polynomial Growth of the Generalized Persistence Diagram

Authors: Donghan Kim, Woojin Kim, and Wonjun Lee

Published in: LIPIcs, Volume 332, 41st International Symposium on Computational Geometry (SoCG 2025)

Abstract
The Generalized Persistence Diagram (GPD) for multi-parameter persistence naturally extends the classical notion of persistence diagram for one-parameter persistence. However, unlike its classical counterpart, computing the GPD remains a significant challenge. The main hurdle is that, while the GPD is defined as the Möbius inversion of the Generalized Rank Invariant (GRI), computing the GRI is intractable due to the formidable size of its domain, i.e., the set of all connected and convex subsets in a finite grid in ℝ^d with d ≥ 2. This computational intractability suggests seeking alternative approaches to computing the GPD. In order to study the complexity associated to computing the GPD, it is useful to consider its classical one-parameter counterpart, where for a filtration of a simplicial complex with n simplices, its persistence diagram contains at most n points. This observation leads to the question: Given a d-parameter simplicial filtration, could the cardinality of its GPD (specifically, the support of the GPD) also be bounded by a polynomial in the number of simplices in the filtration? This is the case for d = 1, where we compute the persistence diagram directly at the simplicial filtration level. If this were also the case for d ≥ 2, it might be possible to compute the GPD directly and much more efficiently without relying on the GRI. We show that the answer to the question above is negative, demonstrating the inherent difficulty of computing the GPD. More specifically, we construct a sequence of d-parameter simplicial filtrations where the cardinalities of their GPDs are not bounded by any polynomial in the number of simplices. Furthermore, we show that several commonly used methods for constructing multi-parameter filtrations can give rise to such "wild" filtrations.
Cite as

Donghan Kim, Woojin Kim, and Wonjun Lee. Super-Polynomial Growth of the Generalized Persistence Diagram. In 41st International Symposium on Computational Geometry (SoCG 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 332, pp. 64:1-64:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{kim_et_al:LIPIcs.SoCG.2025.64,
  author =	{Kim, Donghan and Kim, Woojin and Lee, Wonjun},
  title =	{{Super-Polynomial Growth of the Generalized Persistence Diagram}},
  booktitle =	{41st International Symposium on Computational Geometry (SoCG 2025)},
  pages =	{64:1--64:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-370-6},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{332},
  editor =	{Aichholzer, Oswin and Wang, Haitao},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2025.64},
  URN =		{urn:nbn:de:0030-drops-232162},
  doi =		{10.4230/LIPIcs.SoCG.2025.64},
  annote =	{Keywords: Persistent homology, M\"{o}bius inversion, Multiparameter persistence, Generalized persistence diagram, Generalized rank invariant}
}
Document
DOI: 10.4230/LIPIcs.SoCG.2025.69
Computing Betti Tables and Minimal Presentations of Zero-Dimensional Persistent Homology

Authors: Dmitriy Morozov and Luis Scoccola

Published in: LIPIcs, Volume 332, 41st International Symposium on Computational Geometry (SoCG 2025)

Abstract
The Betti tables of a multigraded module encode the grades at which there is an algebraic change in the module. Multigraded modules show up in many areas of pure and applied mathematics, and in particular in topological data analysis, where they are known as persistence modules, and where their Betti tables describe the places at which the homology of filtered simplicial complexes changes. Although Betti tables of singly and bigraded modules are already being used in applications of topological data analysis, their computation in the bigraded case (which relies on an algorithm that is cubic in the size of the filtered simplicial complex) is a bottleneck when working with large datasets. We show that, in the special case of 0-dimensional homology (relevant for clustering and graph classification) Betti tables of bigraded modules can be computed in log-linear time. We also consider the problem of computing minimal presentations, and show that minimal presentations of 0-dimensional persistent homology can be computed in quadratic time, regardless of the grading poset.
Cite as

Dmitriy Morozov and Luis Scoccola. Computing Betti Tables and Minimal Presentations of Zero-Dimensional Persistent Homology. In 41st International Symposium on Computational Geometry (SoCG 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 332, pp. 69:1-69:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{morozov_et_al:LIPIcs.SoCG.2025.69,
  author =	{Morozov, Dmitriy and Scoccola, Luis},
  title =	{{Computing Betti Tables and Minimal Presentations of Zero-Dimensional Persistent Homology}},
  booktitle =	{41st International Symposium on Computational Geometry (SoCG 2025)},
  pages =	{69:1--69:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-370-6},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{332},
  editor =	{Aichholzer, Oswin and Wang, Haitao},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2025.69},
  URN =		{urn:nbn:de:0030-drops-232219},
  doi =		{10.4230/LIPIcs.SoCG.2025.69},
  annote =	{Keywords: Multiparameter persistence, Zero-dimensional homology, Minimal presentation, Betti table}
}
Document
DOI: 10.4230/LIPIcs.SoCG.2025.10
Steinhaus Filtration and Stable Paths in the Mapper

Authors: Dustin L. Arendt, Matthew Broussard, Bala Krishnamoorthy, Nathaniel Saul, and Amber Thrall

Published in: LIPIcs, Volume 332, 41st International Symposium on Computational Geometry (SoCG 2025)

Abstract
We define a new filtration called the Steinhaus filtration built from a single cover based on a generalized Steinhaus distance, a generalization of Jaccard distance. The homology persistence module of a Steinhaus filtration with infinitely many cover elements may not be q-tame, even when the covers are in a totally bounded space. While this may pose a challenge to derive stability results, we show that the Steinhaus filtration is stable when the cover is finite. We show that while the Čech and Steinhaus filtrations are not isomorphic in general, they are isomorphic for a finite point set in dimension one. Furthermore, the VR filtration completely determines the 1-skeleton of the Steinhaus filtration in arbitrary dimension. We then develop a language and theory for stable paths within the Steinhaus filtration. We demonstrate how the framework can be applied to several applications where a standard metric may not be defined but a cover is readily available. We introduce a new perspective for modeling recommendation system datasets. As an example, we look at a movies dataset and we find the stable paths identified in our framework represent a sequence of movies constituting a gentle transition and ordering from one genre to another. For explainable machine learning, we apply the Mapper algorithm for model induction by building a filtration from a single Mapper complex, and provide explanations in the form of stable paths between subpopulations. For illustration, we build a Mapper complex from a supervised machine learning model trained on the FashionMNIST dataset. Stable paths in the Steinhaus filtration provide improved explanations of relationships between subpopulations of images.
Cite as

Dustin L. Arendt, Matthew Broussard, Bala Krishnamoorthy, Nathaniel Saul, and Amber Thrall. Steinhaus Filtration and Stable Paths in the Mapper. In 41st International Symposium on Computational Geometry (SoCG 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 332, pp. 10:1-10:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{arendt_et_al:LIPIcs.SoCG.2025.10,
  author =	{Arendt, Dustin L. and Broussard, Matthew and Krishnamoorthy, Bala and Saul, Nathaniel and Thrall, Amber},
  title =	{{Steinhaus Filtration and Stable Paths in the Mapper}},
  booktitle =	{41st International Symposium on Computational Geometry (SoCG 2025)},
  pages =	{10:1--10:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-370-6},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{332},
  editor =	{Aichholzer, Oswin and Wang, Haitao},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2025.10},
  URN =		{urn:nbn:de:0030-drops-231625},
  doi =		{10.4230/LIPIcs.SoCG.2025.10},
  annote =	{Keywords: Cover and nerve, Jaccard distance, persistence stability, Mapper, recommender systems, explainable machine learning}
}
Document
DOI: 10.4230/LIPIcs.SOCG.2015.827
Topological Analysis of Scalar Fields with Outliers

Authors: Mickaël Buchet, Frédéric Chazal, Tamal K. Dey, Fengtao Fan, Steve Y. Oudot, and Yusu Wang

Published in: LIPIcs, Volume 34, 31st International Symposium on Computational Geometry (SoCG 2015)

Abstract
Given a real-valued function f defined over a manifold M embedded in R^d, we are interested in recovering structural information about f from the sole information of its values on a finite sample P. Existing methods provide approximation to the persistence diagram of f when geometric noise and functional noise are bounded. However, they fail in the presence of aberrant values, also called outliers, both in theory and practice. We propose a new algorithm that deals with outliers. We handle aberrant functional values with a method inspired from the k-nearest neighbors regression and the local median filtering, while the geometric outliers are handled using the distance to a measure. Combined with topological results on nested filtrations, our algorithm performs robust topological analysis of scalar fields in a wider range of noise models than handled by current methods. We provide theoretical guarantees and experimental results on the quality of our approximation of the sampled scalar field.
Cite as

Mickaël Buchet, Frédéric Chazal, Tamal K. Dey, Fengtao Fan, Steve Y. Oudot, and Yusu Wang. Topological Analysis of Scalar Fields with Outliers. In 31st International Symposium on Computational Geometry (SoCG 2015). Leibniz International Proceedings in Informatics (LIPIcs), Volume 34, pp. 827-841, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)

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@InProceedings{buchet_et_al:LIPIcs.SOCG.2015.827,
  author =	{Buchet, Micka\"{e}l and Chazal, Fr\'{e}d\'{e}ric and Dey, Tamal K. and Fan, Fengtao and Oudot, Steve Y. and Wang, Yusu},
  title =	{{Topological Analysis of Scalar Fields with Outliers}},
  booktitle =	{31st International Symposium on Computational Geometry (SoCG 2015)},
  pages =	{827--841},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-83-5},
  ISSN =	{1868-8969},
  year =	{2015},
  volume =	{34},
  editor =	{Arge, Lars and Pach, J\'{a}nos},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SOCG.2015.827},
  URN =		{urn:nbn:de:0030-drops-51052},
  doi =		{10.4230/LIPIcs.SOCG.2015.827},
  annote =	{Keywords: Persistent Homology, Topological Data Analysis, Scalar Field Analysis, Nested Rips Filtration, Distance to a Measure}
}
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